class_docstr: The minibatch MAC metric.
  This plugin metric only works at training time.
  
  This metric computes the MAC over 1 pattern
  from a single minibatch.
  It reports the result after each iteration.
  
  If a more coarse-grained logging is needed, consider using
  :class:`EpochMAC` instead.
docstr: Creates an instance of the MinibatchMAC metric.
docstr_tok: ["Creates","an","instance","of","the","MinibatchMAC","metric","."]
code: def __init__(self):
      """
      Creates an instance of the MinibatchMAC metric.
      """
      super(MinibatchMAC, self).__init__(
          reset_at="iteration", emit_at="iteration", mode="train"
      )
  
imports: from torch.nn import Module
  from typing import List, Optional
  from torch import Tensor
  from avalanche.evaluation import Metric, PluginMetric, GenericPluginMetric
label_desc: Use image node_id 1 to create a new MinibatchMAC object from inherited base classes: MACPluginMetric with example: obj = MinibatchMAC()